We validated the presence of the two populations by prospective isolation based on newly
identified markers, followed by scRNA-seq. To
isolate these cells by flow sorting, we developed
a panel incorporating surface markers derived
from the set of uniquely expressed genes: FCGR2B/
CD32B for CD1C_A, and CD163 and CD36 for
CD1C_B subsets (Fig. 2B). scRNA-seq of prospectively isolated cells from each subset recapitulated the original split observed in CD1C+ DCs
(Fig. 2C). Unlike monocytes and pDCs, both
CD1C_A and CD1C_B subsets (isolated with the
newly identified markers) were potent stimulators of naïve T cell proliferation (P < 0.05, paired
t test), consistent with the known functional
characteristics of cDCs (Fig. 2D). Activation of
both CD1C subsets with lipopolysaccharide (LPS),
R848 (a TLR7/TLR8 agonist), and polyinosine-polycytidine [poly(I:C)] highlighted functional
differences between these subsets (fig. S3 and
table S4), with CD1C_A secreting higher levels
of the immune mediators CCL19, interleukin-10
(IL-10), IL-12B, and IL-18. Thus, scRNA-seq revealed
unappreciated heterogeneity in this particular
subset, leading to new hypotheses about the
functions of CD1C+ DCs.

Discovering monocyte subsets and their
relationships to DC subsets

Some key genes known to be associated with
monocytes were also expressed by CD1C_B (
cluster DC3) and CD141–CD1C– (cluster DC4) cells
(e.g., CD14 and FCGR3A/CD16, respectively). To
analyze the relationships between monocytes
and DCs, we profiled 372 single blood monocytes
(Fig. 1A and Fig. 3A). On the basis of 339 monocytes that passed QC, we identified four clusters
(Fig. 3B and fig. S4A) distinguished by 102 classifier genes (AUC ≥ 0.85; Fig. 3C, fig. S4B, and
table S5). The two largest clusters, Mono1 and
Mono2, contained the CD14++CD16– (“classical”)
and CD14+CD16++ (“nonclassical”) monocytes, respectively. However, Mono1 and Mono2 also
included 88 of the 124 cells derived from the
“intermediate” monocyte gate (CD14++CD16+)
(fig. S4A), demonstrating that the intermediate
monocytes do not form a homogeneous population. The two smaller clusters, Mono3 and Mono4,
contained 40 of the 124 intermediate cells and
expressed many of the Mono1 (classical monocyte)
signature genes. Mono3 expresses a unique combination of genes that have the potential to affect
cell cycle, differentiation, and trafficking (e.g.,
MXD1, CXCR1, CXCR2, VNN2) whereas Mono4
distinctively expressed a cytotoxic gene signature (e.g. PRF1, GNLY, CTSW ) resembling previously reported “natural killer dendritic cells,”
in addition to coexpressing Mono1 gene set (15–17)
(Fig. 3C and fig. S4B). We conclude that the previously defined classical and nonclassical subtypes
are contained in two distinct clusters (Mono1 and
Mono2, respectively), but that the intermediate
monocytes are far more heterogeneous than previously appreciated, being distributed across two
known and two new clusters (fig. S4A).

Finally, we interrogated the relationship between CD16-expressing CD141–CD1C– cells (cluster
DC4) and CD16+ monocytes (cluster Mono2).
Although the two populations shared many genes
(e.g., FCGR3A), they formed distinct clusters (Fig.
3B) defined by a unique discriminative gene set
(Fig. 3C and tables S7 and S8). DC4 cells were
enriched for type I interferon signaling pathway
(P < 1.53 × 10−13) and response to virus (P < 4.77 ×
10−9) GO terms, whereas Mono2 cells were enriched for immune system process (P < 1.09 × 10−14)
and leukocyte migration (P < 3.57 × 10−8) GO
terms. Although we conclude that monocytes
and DCs are distinct from each other in the steady
state, our data do not address potential interconversion between cell fates or distinct ontogeny.

AXL+SIGLEC6+ population and its
relation to cDCs and pDCs

As described above, a population emerged from
the unbiased cluster analysis (cluster DC5; Fig. 1),
defined by coexpression of unique markers (e.g.,
AXL, SIGLEC1, SIGLEC6, and CD22/SIGLEC2)
(Fig. 4A, fig. S5A, and tables S1 and S2). Flow
cytometry analysis of peripheral blood mononuclear cells (PBMCs) from 10 independent donors confirmed the existence of AXL+SIGLEC6+
cells (“AS DCs”) within the original DC gate
(Fig. 4B) at a frequency of 2 to 3%, consistent
with what was originally observed in the initial scRNA-seq analysis (30 of 768 DCs; Fig. 1C).
scRNA-seq profiling of prospectively sorted AS
DCs (isolated with the gating strategy in Fig. 4B)
showed that the newly sorted cells clustered together with the original cluster (Fig. 4C and fig.

S5B), validating our enrichment strategy.

AS DCs exhibited a spectrum of states basedon gene expression (Fig. 4D) defined by cellsenriched for a pDC-like signature (e.g., IL3RA,IGJ, NRP1, MZB1) and cells enriched for a cDC-like signature (IFI30, ITGAX, LY86, GLIPR2,FGR, LYZ, ENTPD1). We validated this observa-tion by flow cytometry, using the surface markersIL3RA/CD123 and ITGAX/CD11C that respec-tively correlated with pDC and cDC gene signatures(Fig. 4, B and D). We exploited the combinato-rial expression of AXL, SIGLEC6, CD123, andCD11C (at both mRNA and protein levels) toprospectively isolate the ends of this spectrumrepresenting two putative AS DC subtypes (seegating strategy in Fig. 4B), and further validatedtheir identities by scRNA-seq (Fig. 4E and fig. S5,C to F). Across all 10 individuals tested, the two ASDC subpopulations represented a very small frac-tion of the Lin–HLA-DR+ populations (Fig. 4F).Notably, lower levels of AXL and SIGLEC6 proteinwere associated with increased HLA-DR, CD11C,and CD1C, whereas higher levels of AXL andSIGLEC6 were associated with increased CD123,CD303, and CD141 and decreased HLA-DR (fig.S5, C to J). This latter relationship was also ob-served by t-SNE analysis of flow cytometry data,where a peninsula with graded expression of ASDCs was located at the base of the CD1C+ DCcluster and adjacent to the pDC cluster (Fig. 4G).Trajectory mapping of these cells across differentlevels of the surface markers CD123 and CD11Cfurther indicated that AS DCs form a continuumfrom a pDC transcriptional state to a CD1C+ DCtranscriptional state (fig. S5, C to F). Taken to-gether, our data suggest that AXL+SIGLEC6+DCs are related but not identical to cDCs or pDCs.

pDCs are phenotypically and
functionally distinct from CD123+CD11C–

AS DCs

Because pDCs and AXL+SIGLEC6+CD123+CD11C–/lo
DCs shared expression of many genes (Fig. 4, D
and E, and fig. S6A), we assessed whether these
cell types also shared functional properties. We
found that the genes specifically expressed by
pDCs, but not by AS DCs, were associated with
the known biological properties of pDCs. This
includes, for example, genes associated with pathogen sensing and induction of type I interferons (IRF7, TLR7, SLC15A4, and PACSIN1), secretion
(e.g., DERL3, LAMP5, and SCAMP5), and the pDC
master regulator transcription factor TCF4, along
with its binding targets (e.g., SLA2, PTCRA,
PTPRCAP) (Fig. 5A and fig. S6A) (18, 19). In contrast, CD123+CD11C–/lo AS DCs expressed cDC
markers, including CD2, CX3CR1, CD33/SIGLEC3,
CD5, and SIGLEC1/CD169, both at protein and
mRNA levels (Fig. 5A and fig. S6, A to C). pDCs
were also morphologically distinct from AS DCs.
Both AS DC subsets possessed the same cerebri-form nucleus and cytoplasmic features of cDCs (Fig.
5B). We hypothesized that although CD123+CD11C–/lo
AS DCs expressed pDC markers, including IL3RA/
CD123 and CLEC4C/CD303 (fig. S5, G to J), they are
functionally distinct from pDCs.

To compare the functional properties of “pure”
pDCs to AS DCs and cDCs, we used the markers
identified in our study to isolate pure pDCs by
excluding AS DCs, CLEC9A+ DCs, CD1C+ DCs,
and monocytes by FACS. As expected, pure pDCs
produced their hallmark cytokine, interferon-a
(IFN-a), while AS DCs produced negligible amounts
of IFN-a upon Toll-like receptor 9 (TLR9) stimulation (P < 0.001; Fig. 5C). In contrast, the
CD123loCD11C+ AS DC subset secreted IL-12p70
at similar levels to other cDCs, while pure pDCs
and CD123hiCD11C–/lo AS DCs did not produce
IL-12p70 (P < 0.01; Fig. 5C). Other factors, such
as IL-8, were produced at high levels by the
CD123+CD11C–/lo AS DC subset but not by pDCs
Villani et al., Science 356, eaah4573 (2017) 21 April 2017 5 of 12
RESEARCH | RESEARCH ARTICLE